SOTAVerified

Inverse Rendering

Inverse Rendering is the task of recovering the properties of a scene, such as shape, material, and lighting, from an image or a video. The goal of inverse rendering is to determine the properties of a scene given an observation of it, and to generate new images or videos based on these properties.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 226–250 of 271 papers

TitleStatusHype
Identity-Expression Ambiguity in 3D Morphable Face Models—0
Learning Indoor Inverse Rendering with 3D Spatially-Varying Lighting—0
Spatially and color consistent environment lighting estimation using deep neural networks for mixed reality—0
Differentiable Surface Rendering via Non-Differentiable Sampling—0
Modeling Clothing as a Separate Layer for an Animatable Human Avatar—0
Joint Learning of Portrait Intrinsic Decomposition and Relighting—0
NormalFusion: Real-Time Acquisition of Surface Normals for High-Resolution RGB-D Scanning—0
OpenRooms: An Open Framework for Photorealistic Indoor Scene Datasets—0
Deep Direct Volume Rendering: Learning Visual Feature Mappings From Exemplary Images—0
Spectral MVIR: Joint Reconstruction of 3D Shape and Spectral Reflectance—0
PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting—0
Neural Lumigraph RenderingCode0
Deep Learning compatible Differentiable X-ray Projections for Inverse Rendering—0
Uncalibrated Neural Inverse Rendering for Photometric Stereo of General Surfaces—0
MaterialGAN: Reflectance Capture using a Generative SVBRDF Model—0
Object-based Illumination Estimation with Rendering-aware Neural Networks—0
Single-Shot Neural Relighting and SVBRDF Estimation—0
OpenRooms: An End-to-End Open Framework for Photorealistic Indoor Scene Datasets—0
Polarimetric Multi-View Inverse Rendering—0
Q-NET: A Network for Low-Dimensional Integrals of Neural Proxies—0
Non-Line-of-Sight Surface Reconstruction Using the Directional Light-Cone Transform—0
Inverse Rendering Techniques for Physically Grounded Image Editing—0
A Bayesian Inference Framework for Procedural Material Parameter Estimation—0
Refining 6D Object Pose Predictions using Abstract Render-and-Compare—0
Deep Single-Image Portrait RelightingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Neural-PBIRHDR-PSNR26.01—Unverified
2NVDiffRecMCHDR-PSNR24.43—Unverified
3InvRenderHDR-PSNR23.76—Unverified
4NeRFactorHDR-PSNR23.54—Unverified
5NeRDHDR-PSNR23.29—Unverified
6NVDiffRecHDR-PSNR22.91—Unverified
7PhySGHDR-PSNR21.81—Unverified